AI Economics

Turn AI spend into measurable business value

See every dollar. Control every investment.

Yarken connects AI Usage, Spend and Ownership to Business Value. One financial model, so every AI dollar can be allocated, governed, and tied to a business outcome.

1
Total AI costToken, licences, labor and cloud costs
2
Clear ownershipVendors, apps, initiatives, teams and services
3
AI unit economicsCost per request, seat, workload, and outcome
4
Governed actionsForecast, allocate, explain, and optimize

AI capitalization

Traceable AI capital decisions

AI development costs sit across cloud services, model APIs, software, internal labor, contractors, data, and specialist vendors. Yarken brings those costs into one governed model and connects them to the products, initiatives, owners, and development stages that created them.

01

Identify the full cost base

Bring together GL, cloud, contracts, invoices, labor, project, and usage data.

02

Connect cost to accountable work

Allocate spend to products, initiatives, teams, applications, and business units.

03

Create decision-ready evidence

Maintain a consistent financial record that supports capitalization assessment, governance, forecasting, and audit preparation.

Ask Yarken

Which AI issue is your team facing?

Ask the question behind the dashboard. Yarken applies your financial model, business context, and operating rules to explain what changed, why it changed, and what should happen next.

Talk to an expert
Yarken

01

Compute

Bedrock, Azure OpenAI, Vertex AI, GPUs, and specialist infrastructure.

02

Tokens

OpenAI, Anthropic, Google, Cohere, and other model providers.

03

Licenses

Copilot, Agentforce, Now Assist, Cursor, and AI-enabled SaaS.

04

Labor data

Internal teams, contractors, labeling, training, and operations.

05

Vendors

Consulting, existing SaaS licences, AI data licences and specialist AI tools.

The problem

Tokenomics and cloud bills are only the start

Cloud shows one slice. The full cost of AI now sits across five disconnected categories, owned by different teams and measured in different ways.

Cloud bills show one. Yarken brings all five together.

Governed AI Economics

One connected model for usage, spend, and value

Bring fragmented AI Economics into one governed system to understand AI Spend versus Business Value.

AI Cost

Build a fully loaded view across compute, tokens, licenses, contracts, labor, and data.

Cloud costsGLInvoicesContracts

AI Usage

Understand adoption and consumption across models, workloads, teams, seats, calls, and GPU hours.

TokensCallsGPU hoursSeats

Business Value

Connect AI investment to productivity, revenue, efficiency, quality, and business outcomes.

ProductivityRevenueROIOutcomes

Decision-ready AI unit economics

AI Total Cost
$4.14M
↑ 12.8%vs last month
Shadow AI Cost
$342K
↑ 7.1%vs last month
Capitalization Rate
26%
↑ 4 ptsvs last month
Qualifying Cap Amount
$1.08M
↑ 18.3%vs last month
Variable AI Spend
$2.76M
↑ 21.4%vs prior year
End of Year Projected
$49.7M
↑ 16.2%vs prior year

How it works

From scattered inputs to Governed AI Economics

Bring fragmented AI Economics into one governed system to understand AI Spend versus Business Value

01

Connect

Bring together cloud cost, APIs, SaaS, contracts, GL, labor, invoices, and usage data.

02

Model

Normalize spend into a governed TBM and FinOps-aligned model.

03

Allocate

Assign cost to apps, services, teams, initiatives, and business units.

04

Control

Track budget forecasts, variances, showback, cross-charges and unit economics.

The architecture for AI Economics. Three inputs — AI cost, AI usage, and Business Value — feed one governed model that outputs AI unit economics: cost per 1K tokens, per request, per active seat, per outcome, and value per dollar.
From disconnected AI spend to governed financial clarity. Ingest, normalize, allocate, explain, act

Platform capabilities

Six capabilities. One system

Move from fragmented cost visibility to governed AI economics across leadership, finance, engineering, and FinOps teams.

Adoption + governance

See ownership, classification, concentration, production status, and activity outside approved channels.

AI-powered allocation

Use explainable suggestions and governed rules to map fragmented spend to accountable owners and outcomes.

Squad-level intelligence

Understand cost by squad, member, model, environment, technology tower, and use case.

Agentic automation

Build governed specialist agents and playbooks that assist execution while keeping people in control.

Ask Yarken

Ask questions in natural language and receive a structured observation, root cause, and recommendation.

Executive overview

Track AI spend against budget, project year-end run rate, and connect investment to realized business value.

Governance outcomes

The AI Economics questions facing every organization

Yarken connects spend to ownership, ownership to business context, and business context to action.

01

What are we spending on AI?

02

Who owns it, and where?

03

What value is it creating?

04

What should we do next?

AI Economics packages

Choose the right starting point for AI Economics

Start with cost visibility, govern usage and ownership, and connect AI investment to business value.

Control

See and control AI cost.

Best for

Teams that need one trusted view of AI spend before it gets out of control.

  • AI cost data ingestion (financial + operational)
  • Multiprovider cost normalisation
  • AI cost taxonomy — 5 cost categories
  • Cost attribution & allocation methods
  • Attribution by function, team & use case
  • Chargeback & showback reporting
  • Tooling utilisation & overlap
  • Budget setting with alerts
  • Anomaly detection
  • Cost optimisation recommendations (Ask Yarken)
  • Shadow AI discovery
  • Ownership dimension
  • Cost forecasting
  • Budget enforcement
  • AI workforce cost view
  • Initiative & product economics
  • Unit economics & cost per outcome
  • Model benchmarking
  • Cost vs. realised value
  • AI Capex / Opex treatment
Talk to us

Custom pricing and implementation options available.

Forecast

Govern usage, ownership and forecast.

Best for

Organizations that need to understand who is using AI, where it's being used, forecast budgets, and where governance gaps exist.

  • AI cost data ingestion (financial + operational)
  • Multiprovider cost normalisation
  • AI cost taxonomy — 5 cost categories
  • Cost attribution & allocation methods
  • Attribution by function, team & use case
  • Chargeback & showback reporting
  • Tooling utilisation & overlap
  • Budget setting with alerts
  • Anomaly detection
  • Cost optimisation recommendations (Ask Yarken)
  • Shadow AI discovery
  • Ownership dimension
  • Cost forecasting
  • Budget enforcement
  • AI workforce cost view
  • Initiative & product economics
  • Unit economics & cost per outcome
  • Model benchmarking
  • Cost vs. realised value
  • AI Capex / Opex treatment
Talk to us

Custom pricing and implementation options available.

Also available as 3rd-party integrations (not included in any package): intelligent model routing, token and context efficiency optimization, and developer experience & integrations.

Need help choosing? Reach out to our experts to find the right starting point based on your AI maturity, governance needs, and value goals. Talk to us

Trusted by enterprises. Built for Finance

Yarken is live with enterprise technology teams governing complex spend across cloud, SaaS, infrastructure, labor, applications, and AI.

Enterprise-grade trust

SOC 2 compliant, FinOps Certified, aligned with the TBM Council, a member of Tokenomics Foundation, and recognized by Gartner as an established ITFM vendor.

SOC 2
FinOps Foundation
TBM Council
Gartner
Tokenomics Foundation

One platform. Proven foundation

Yarken combines cost intelligence, planning, contracts, application TCO, showback, chargeback, FinOps, and AI Economics in one governed platform.

Talk to Yarken

Get clarity on your AI spend

If AI costs are growing faster than your ability to explain them, Yarken can help. We connect AI usage, spend, ownership, and value in one governed financial model.

Understand fully loaded AI cost across cloud, tokens, licenses, labor, and vendors.
Assign spend to accountable teams, initiatives, applications, and business units.
Build the financial context needed to govern investment and prove value.

Request an AI Economics review

Tell us what you are trying to understand. We will follow up with the right Yarken specialist.